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EchoLedger

by io.github.icmoore

CalculateSlippage

Calculate slippage and price-impact decomposition for a proposed swap on a Uniswap V2 or V3 pool. Returns spot vs execution price, slippage percentage, slippage cost in output-token units, and price impact. Also returns the maximum trade size that stays within 1% slippage for V2 pools; V3 returns null for that field because tick-crossing math has not yet been inverted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rpc_urlYesAn Ethereum (or L2) JSON-RPC URL used to read live pool state. Required; supplied by you per call (BYO-RPC) and may carry your provider key. The endpoint stores and logs nothing — the URL is never persisted or written to logs.
chain_idNoOptional guard. If supplied and the RPC reports a different chain id, the call is rejected. Defaults to 1 (Ethereum mainnet) conceptually; omit to skip the check.
lwr_tickNoLower tick of the position (V3 only; null for V2).
upr_tickNoUpper tick of the position (V3 only; null for V2).
amount_inNoAmount of token_in to trade, in human units. Must be > 0.
pool_typeYesWhich protocol the pool at pool_address belongs to. This tool accepts uniswap_v2 | uniswap_v3.
amounts_inNoOptional batch form of 'amount_in': an array of values to evaluate in a single call. The pool is read once and the result is an array with one entry per element, in input order. Supply EITHER 'amount_in' (single) OR 'amounts_in' (batch), not both. Max 256 entries.
block_numberNoOptional block number to pin the read to a historical block. Omit to read the latest block.
pool_addressYesOn-chain address of the pool/pair to analyze (Uniswap V2/V3 pair, Balancer weighted pool, or Curve stableswap pool). Required. Lowercase, uppercase, or checksum casing all work.
token_in_nameYesSymbol of the input token for the trade (e.g. 'USDC', 'WETH'). Must be one of the two tokens in the pool.

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly lists what is returned (spot vs execution price, slippage percentage, slippage cost, price impact) and discloses a meaningful limitation: V3 returns null for the maximum trade size because tick-crossing math has not been inverted. This goes beyond a mere statement of function.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with purpose. Sentence 1 states what it does, sentence 2 enumerates the outputs, and sentence 3 explains the V2/V3 difference. Every sentence carries essential information, with no filler or repetition. This is exemplary conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description must convey return values; it does so by listing all key metrics. It also covers the V3 null behavior. It does not specify the exact output structure (e.g., field names or units) beyond 'output-token units', but for a calculation tool this level of detail is adequate. The parameter side is fully covered by the schema, so the description is sufficient for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description itself adds no parameter-level detail beyond what the schema already provides. It mentions the maximum trade size result, but that is an output, not a parameter. The schema descriptions are already rich (e.g., rpc_url privacy, amount_in human units), so the description does not need to compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Calculate slippage and price-impact decomposition for a proposed swap on a Uniswap V2 or V3 pool.' This clearly states what the tool does and distinguishes it from sibling analysis tools like AnalyzePosition or CheckPoolHealth, which focus on positions or pool health rather than swap execution metrics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: use this tool when you have a proposed swap on a Uniswap V2 or V3 pool and need slippage/price-impact decomposition. It does not explicitly mention alternatives or when-not-to-use, but the specific 'proposed swap' framing makes the intended use case evident. Sibling tools exist, but the description gives enough context to choose appropriately.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.2/5.0
Disambiguation4/5

Tools are mostly distinct by protocol and action, but AnalyzePosition and the protocol-specific Analyze*LP tools overlap in purpose, as do SimulatePriceMove and Simulate*Move. Descriptions clearly differentiate them, so an agent can select correctly with careful reading, but the generic versus specific split introduces some ambiguity.

Naming Consistency5/5

All tool names follow a consistent VerbNoun pattern (Analyze, Assess, Build, Calculate, Check, Detect, Simulate) with no mixing of conventions. The naming is uniform and predictable across the entire set.

Tool Count5/5

11 tools is well within the ideal range for a specialized LP analysis server. Each tool covers a distinct function across protocols, and none feel redundant or superfluous. The count is well-scoped for the server's purpose.

Completeness4/5

The tool set covers the full lifecycle of LP analysis: position PnL analysis, price simulations, depeg risk, slippage, pool health, rug detection, and state serialization. Minor gaps exist, such as fee attribution for Balancer and Curve pools and a generic simulate tool for all protocols, but these are protocol limitations or acceptable omissions.

Resources